4.7 Article

Spatiotemporal variation in near-surface CH4 concentrations in China over the last two decades

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 28, Issue 34, Pages 47239-47250

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-14007-0

Keywords

Methane; Atmospheric chemistry model; CAM-chem model; Multiple Gaussian functions; Spatiotemporal variations; China

Funding

  1. Key Programin the Youth Elite Support Plan in Universities of Anhui Province [gxgwfx2019058]
  2. Key University Science Research Project of Anhui Province [KJ2019A0632, KJ2019A0633]
  3. Key Research Projects of Provincial Humanities and Social Sciences in Colleges and Universities [SK2017A0409, SK2018A0426]
  4. National Undergraduate Training Program for Innovation and Entrepreneurship [2019CXXL044]

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The study demonstrates the reliability of estimating near-surface methane concentrations in China using a Gaussian function model based on data simulated by an atmospheric chemical model. From 2001 to 2019, there was an increasing trend in near-surface methane concentration in China, with a higher concentration in the east compared to the west, and a higher concentration in the north compared to the south. The spatial distribution of methane concentrations align with the Hu Huanyong population line division in China.
Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface CH4 concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface CH4 concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20 +/- 0.23 ppb center dot a(-1). The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line.

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